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Center on Positive Behavioral Interventions and Supports, 2022
This practice guide is an updated version of "Supporting and Responding to Behavior: Evidence-based Classroom Strategies for Teachers" (see ED619696) that replaces, rather than supplements, the first version. This guide summarizes evidence-based, positive, and proactive practices that support and respond to students' social, emotional,…
Descriptors: Evidence Based Practice, Student Behavior, Intervention, Classroom Techniques
Office of Special Education Programs, US Department of Education, 2015
The purpose of this document is to summarize evidence-based, positive, proactive, and responsive classroom behavior intervention and support strategies for teachers. These strategies should be used classroom-wide, intensified for support small-group instruction, or amplified further for individual students. These strategies can help teachers…
Descriptors: Evidence Based Practice, Student Behavior, Intervention, Positive Behavior Supports
Burns, Matthew K.; Scholin, Sarah E.; Kosciolek, Stacey; Livingston, Judy – Journal of Psychoeducational Assessment, 2010
The current study examines the consistency of two response-to-intervention (RTI) decision-making models. Weekly progress monitoring data for 30 students participating in a Tier II intervention were collected for 30 weeks. The data were examined by comparing them to an aimline with a yearly goal and by computing a dual discrepancy (DD) using…
Descriptors: Reading Achievement, Reading Tests, Data Collection, Responses
Griffiths, Amy-Jane; VanDerHeyden, Amanda M.; Parson, Lorien B.; Burns, Matthew K. – Assessment for Effective Intervention, 2006
Several approaches to response to intervention (RTI) described in the literature could be blended into an RTI model that would be effective in the schools. An effective RTI model should employ three fundamental variables: (a) systematic data collection to identify students in need, (b) effective implementation of interventions for adequate…
Descriptors: Responses, Intervention, Data Collection, Models